Statistical analysis of a subspace method for blind channel identification

Abstract
This paper considers the problem of blind channel estimation of multi-channel FIR filters. This is a problem arising in, for example, mobile communication systems using digital signalling. By using the orthogonality property between the noise subspace and the channel matrix, it has been shown in earlier work that the channel matrix is identifiable up to a multiplicative constant. In this article, the asymptotic properties of a subspace method using this orthogonality property is presented. An asymptotically correct weighting matrix is derived, demonstrating an attainable lower theoretical bound using the subspace estimate.

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